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Automatically extract info from Granger causality output

4 messages · Pfaff, Bernhard Dr., Ivan

Ivan
# 
Dear Community,

this is my first programming in R and I am stuck with a problem. I
have the following code which automatically calculates Granger
causalities from a variable, say e.g. "bs" as below, to all other
variables in the data frame:

log.returns<-as.data.frame( lapply(daten, function(x) diff(log(ts(x)))))
y1<-log.returns$bs
y2<- log.returns[,!(names(log.returns) %in% "bs")]
Granger<- function(y1,y2) {models=lapply(y2, function(x)
VAR(cbind(x,y1),ic="SC") ); results=lapply(models,function(x)
causality(x,cause="y1")); print(results)}
Count<-Granger(y1,y2)

which produces the following output (I have printed only part of it
(for Granger causality of bs on ml)):

$ml
$ml$Granger

        Granger causality H0: y1 do not Granger-cause x

data:  VAR object x
F-Test = 0.2772, df1 = 1, df2 = 122, p-value = 0.5995


$ml$Instant

        H0: No instantaneous causality between: y1 and x

data:  VAR object x
Chi-squared = 19.7429, df = 1, p-value = 8.859e-06

My questions:

1)How can I edit the function above so that the output writes: Granger
causality H0: bs do not Granger-cause ml   rather than  Granger
causality H0: y1 do not Granger-cause x?

2) I want to extract the p-values of the tests into a data frame for
instance. The problem is that the output has a 3 layer structure.
Thus, for the above p-value I need to write count$ml$Granger$p.value.
I thought of a loop of something like for(i in 1:length(count))
{z=count$[[i]]$Granger$p.value} but it didn't work.

Thank you very much for your help.

Best Regards.
Pfaff, Bernhard Dr.
# 
Dear Ivan,

first, it would pay-off in terms of readability to employ line breaks and second to provide a reproducable code snippet and third which package you have used. Now to your questions:
1) What happens if you provide colnames for your objects?
2) What happens if you omit the $ after count?

Best,
Bernhard

ps: the function seems to have been ported from the package 'vars'. In this package the function causality() is included which returns a named list with elements of class htest.
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Ivan
# 
Dear Bernhard,

thank you very much for the response. Yes, I am using the packsges
"vars" with fuchrions VAR() and causality().

1)Giving colnames to the objects does unfortunately not  change anything.

2) I am not sure if I understood you right. Did you mean to insert
Countml$Granger$p.value rather than  Count$ml$Granger$p.value? This
returns: Error: Object 'Countms' not found.

By the way, str(Count) produces the following:
List of 4
 $ ml:List of 2
  ..$ Granger:List of 5
  .. ..$ statistic: num [1, 1] 0.277
  .. .. ..- attr(*, "names")= chr "F-Test"
  .. ..$ parameter: Named num [1:2] 1 122
  .. .. ..- attr(*, "names")= chr [1:2] "df1" "df2"
  .. ..$ p.value  : num [1, 1] 0.6
  .. ..$ method   : chr "Granger causality H0: y1 do not Granger-cause x"
  .. ..$ data.name: chr "VAR object x"
  .. ..- attr(*, "class")= chr "htest"
  ..$ Instant:List of 5
  .. ..$ statistic: num [1, 1] 19.7
  .. .. ..- attr(*, "names")= chr "Chi-squared"
  .. ..$ parameter: Named int 1
  .. .. ..- attr(*, "names")= chr "df"
  .. ..$ p.value  : num [1, 1] 8.86e-06
  .. ..$ method   : chr "H0: No instantaneous causality between: y1 and x"
  .. ..$ data.name: chr "VAR object x"
  .. ..- attr(*, "class")= chr "htest"
 $ jp:List of 2
.
.
.
.

Best Regards,

Ivan

On Fri, Apr 15, 2011 at 10:13 AM, Pfaff, Bernhard Dr.
<Bernhard_Pfaff at fra.invesco.com> wrote:
Pfaff, Bernhard Dr.
# 
Hello Ivan,

see example(causality) for the first question and use count[[i]] and not count$[[i]] for the second. The following works for me:

example(causality)
test1 <- causality(var.2c, "e")
test2 <- causality(var.2c, "prod")
tl <- list(test1, test2)
res <- matrix(NA, ncol = 1, nrow = length(tl))
for(i in 1:length(tl)){
	res[i, ] <- tl[[i]]$Granger$p.value
}
res

hth,
Bernhard